|Fig. 1: A sample QR Code. Source: Wikimedia Commons|
|Fig. 2: The mobile tagging process in action. Source: Wikimedia Foundation|
Mobile Tagging systems, like QR Codes (see Fig. 1) and Microsoft Tag, have increased in popularity in recent years with improved smartphone penetration in the United States.  These tagging systems promise a new interactive mechanism for advertisers and other sales representatives to reach out to an audience.  While there are numerous other uses for mobile tagging systems, advertising has become the most common use for them at this time. 
So how does mobile tagging work? Mobile tagging requires three parts to work properly: a smartphone with barcode-reading software installed, a tag or barcode, and a piece of data that is to be transmitted (See Fig. 2). An advertiser can plaster these tags anywhere, and whenever a user wants to find out more information about the tag, they open the barcode reading software on their phone and viola- they are redirected to the information that the advertiser intended to be opened. This can be used very effectively by real estate agents, who don't have enough space on pamphlets to contain all the details about the house, but they can redirect a user to that information found somewhere else.
This information retrieval mechanism is not without flaws. Barcode readability is affected by numerous factors, including shadows, blurring, rotation errors, and imperfect lighting conditions, among other factors.  These readability concerns often frustrate users, who in turn disregard future mobile tags. Perhaps most importantly, the ubiquity of smartphone-enabled barcode readers has created a new security problem- now anyone with access to a smartphone can read almost all barcodes found anywhere.
In February of 2011, a Disney employee was experimenting with his cell phone's barcode scanner, when he happened to read the barcode printed on his ID badge.  He was shocked to find that his barcode contained his full social security number. This wouldn't have posed a problem before the introduction of the mobile tagging system, but with the ubiquity of smartphone barcode scanners, this is a huge problem. Employers must be very cautious when dealing with employee badges that contain sensitive information. On the other hand, mobile tagging, if done properly, can allow for increased security features that traditional barcodes do not allow for.
There are many problems with current barcode readers, but one of the most interesting is the problem of counterfeit goods. Particularly medicines, which pose not only a profit loss for the company, but also a potential health hazard to society.  Recently introduced barcoding methodologies and digital watermarking algorithms allow for a new layer of security on top of existing barcodes. [5-7] This means that a barcode reader has to read both a key and a barcode in order to unlock the data behind it. This allows, for example, invisible inks to be used on a barcode to prevent counterfeiters. What this allows is that a specific batch of medicine can be barcoded with a unique key, which changes depending on the batch. If a counterfeiter attempts to copy the barcode and place counterfeit drugs into the supply chain, the key will not match correctly (invisible ink cannot be copied by a simple copier), and thus alert the authorities about its fraudulent nature.
We are in a new age of experimentation and innovation in the barcoding industry. We can expect numerous advancements in barcoding to start affecting our everyday lives, with improvements ranging from the fradulent medication case outlined above to numerous social tasks that can be made easier with barcodes. 
© Salahodeen Abdul-Kafi. The author grants permission to copy, distribute and display this work in unaltered form, with attribution to the author, for noncommercial purposes only. All other rights, including commercial rights, are reserved to the author.
 H.-C. Huang and W.-C. Fang, eds. Intelligent Multimedia Data Hiding (Springer, 2007).
 H.-C. Huang, F.-C. Chang and W.-C. Fang, "Reversible Data Hiding With Histogram-Based Difference Expansion For QR Code Applications," IEEE Trans. Consumer Electronics 57, 779 (2011).
 Y. Kato et al., "Low Resolution QR-Code Recognition by Applying Super-Resolution Using the Property of QR-Codes," Intl Conf. on Document Analysis and Recognition ICDAR, 992 (2008).
 L. Coady, " Disney ID cards Risk Identity Theft, Violate Employee Privacy, Suit Says," Thompson Reuters News and Insights, 17 Mar 11.
 S. Agaian et al., "Fused Fibonacci-Like (p,q) Sequences With Compression and Barcoding Applications," Proc. SPIE 8304, 83040E (2012).
 S. Agaian, "Fused Number Representation Systems and Their Barcode Applications," Proc. SPIE 7542, 754207 (2010).
 S. Vongpradhip and S. Rungraungsilp, "QR Code Using Invisible Watermarking in Frequency Domain," Proc. 9th Intl. Conf. on ICT and Knowledge Engineering", 47 (2012).